Urme Bose

Machine learning · Behaviour · Biosignals · Digital health

Machine learning engineer and behavioural researcher.

CNRS and Erasmus Mundus training in multimodal sensing, longitudinal data and predictive modelling.


Selected Projects

CalmSense: current static benchmark dashboard

CalmSense

Wearable stress benchmark.

  • 15 subjects · 58 saved features · LOSO.
  • RF binary accuracy 0.910, averaged across subjects.
  • Static results; no significant feature-model differences.

WESAD · LOSO · SHAP · Calibration

PulseShift 2024 held-out ROC curves

PulseShift

Bike-share demand suppression forecast.

  • 26,288 panel hours; 2024 unweighted holdout AUROC 0.936, ECE 0.044.
  • Open-Meteo/CAMS; exclude heat index ≥103°F or AQI ≥150.
  • Individual activity and health benefits unmeasured.

Demand · Weather · AQI · Logistic

NovaVision saved pilot recovery accuracy with bootstrap 95% intervals

NovaVision

Text-to-image emotion pilot.

  • 7 classes · 256 px · CPU.
  • No conditioning tier passes Holm correction.
  • Probe collapse; correction limited to 5/7 classes.

Affect · SD-Turbo · CLIP · Evaluation

NexusRAG SciFact 300 and NFCorpus 323-query retrieval results

NexusRAG

Local search and cited answers.

  • PDF/DOCX/MD/TXT → LanceDB + BM25 → Ollama.
  • PRF once below 0.55 similarity; NLI optional.
  • Citation indices checked; claims need review.

RAG · LanceDB · BM25 · Ollama

Multimodal-Multisensor: participant wearing eye-tracking glasses during a data-collection session

Multimodal-Multisensor

Longitudinal eye-tracking and HRV study.

  • 10 adults · 3 weekly sessions.
  • ICC(1) 0.22–0.61 across reported measures.
  • Reported HRV interval crosses zero; underpowered.

Longitudinal · Eye-tracking · HRV · ICC


Academic Services

  • Conference Reviewer: CYPSY 2023, ICASSP 2026
  • Journal Reviewer: IEEE